Senior Data Scientist - FDE

Microsoft
U.S. / San Francisco Bay area / New York City metropolitan area2026-08-11onsite

About the job

In the Microsoft Frontier Company Engineering team, you won’t just build software; you’ll deliver real outcomes for some of the world’s most complex organizations. We are a global team of world-class engineers who have been working in a Forward Deployed Engineering (FDE) model for more than a decade, embedding directly within customer teams to solve their toughest challenges, side-by-side, and shipping production-ready solutions in days, not months. As a Senior Data Scientist, you will help transform how organizations use data, developing models, running experiments, and driving evidence-based decisions that have measurable business impact. You’ll work in small, multidisciplinary crews alongside engineers, product managers, and domain experts, owning the full lifecycle from data discovery through to deployed solutions. Our work is powered by AI, applying the mindset and tooling across the entire development lifecycle to move from idea to production in days while maintaining the highest standards of security, quality, and trust.

Responsibilities

Oversee acquisition of data sets necessary for project delivery, ensure proper formatting/description, address gaps, and drive ethics and privacy discussions around data collection and preparation.

Evaluate team models using metrics tied to business outcomes, recommend improvements, drive best practices, develop operational models at scale, conduct reviews of analysis/modeling techniques, and identify/invent new evaluation methods.

Research and maintain deep industry knowledge (trends/technologies) to identify strategy opportunities, contribute to thought leadership, write extensible code spanning multiple features, and develop expertise in debugging techniques.

Define business, customer, and solution strategy goals, partner with teams to explore new opportunities, and offer pragmatic customer-oriented solutions aligned with data capabilities.

Coach engineers and cross-disciplinary partners in data science best practices and scale knowledge within the cross-discipline team.

Qualifications

Minimum

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.

Preferred

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 6+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.

Experience partnering directly with customers or internal stakeholders to deliver solutions end-to-end.